US20020116171A1 - Interactive tool for semi-automatic creation of a domain model - Google Patents

Interactive tool for semi-automatic creation of a domain model Download PDF

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US20020116171A1
US20020116171A1 US09/785,893 US78589301A US2002116171A1 US 20020116171 A1 US20020116171 A1 US 20020116171A1 US 78589301 A US78589301 A US 78589301A US 2002116171 A1 US2002116171 A1 US 2002116171A1
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Dale Russell
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Abstract

A method, system and program product 100 usable by domain developers having any experience level in creating domain models. A representation of domain model knowledge is derived from a domain specification. The domain specification includes multiple potential domain objects, e.g., tables of APIs functional arguments, and each of the potential domain objects include one or more attributes. Potential domain objects are selected one at a time 102 from the specification and offered to the developer. The developer decides 104 whether or not to include the potential domain object in the domain model. If the developer decides to include the potential domain object 106, then the system provides a default name 108, i.e., the table name or argument name, and allows the developer to rename the selected domain object 110. Then, after having selected the object, potential attributes 112, e.g., table columns 1122, are selected from the object and offered to the developer 116. If the developer decides to include a potential attribute, then a default name, i.e., the column name or name extracted from an API function, is offered 1126 for the selected attribute and the developer is allowed to rename attributes 1128. Once all the potential domain objects have been offered 118 to the developer and the developer has either decided to include the potential objects or not, the system checks the domain model for nesting structure 200. If domain objects include attributes that are shared with other domain objects 2006, then those domain objects may be reorganized such that some domain objects include instances of identically named attributes from other domain objects.

Description

    RELATED APPLICATION
  • The present invention is related to U.S. patent application Ser. No. 09/______ (Attorney Docket No. CML00012H) entitled “An Interactive Tool for Semi-Automatic Creation of a Natural Language Grammar from a Domain Model” to Dale W. Russell, filed coincident herewith and assigned to the assignee of the present application.[0001]
  • BACKGROUND OF THE INVENTION
  • 1. Field of the Invention [0002]
  • The present invention is related to language dialog systems and, more particularly to domain model creation for natural language dialog systems. [0003]
  • 2. Background Description [0004]
  • In the development of spoken or natural language dialog systems, a representation, referred to as a domain model, is used in the creation of grammars, dialog managers and other system components. The domain model provides a useful, formalized representation of knowledge about the domain of an application that the system is addressing and reflects a particular domain expert's conceptualization of that knowledge. [0005]
  • Previously, domain models were handcrafted by the particular domain expert and crafting required substantial time and specialized expertise. Model development focus was directed to the acquisition of procedural knowledge for use by expert systems. Such knowledge was acquired and maintained in the form of rules for encoding instructions. The instructions were provided to the expert system and were the selected response for performing a given action under a given set of conditions. These methods all require a substantial amount of an expert's time. [0006]
  • To that end, tools are being developed to facilitate domain model development. One such tool is the LOOM knowledge representation system from Sun Microsystems which is a toolkit for the development of domain models by domain experts. A state of the art project that is based on LOOM is a domain model development toolkit called EXPECT. EXPECT uses the LOOM framework to construct domain models and provide an intuitive interface. However, to use EXPECT a domain expert must construct the ontology of the domain from scratch. [0007]
  • Typically, the goal in expert systems is to capture an expert's knowledge in computer usable form. In particular procedural knowledge is captured and used for predicting likely responses in particular given situations, such as how to diagnose a disease or how to effect auto repairs. Declarative knowledge is required to create grammars and other spoken dialog components used in spoken language dialog expert systems. [0008]
  • However, in creating spoken language dialog components for such systems, domain models are not explicitly created and, instead, grammars or speech models are induced directly. This direct induction approach requires inputting a corpus of training examples. In grammar development, the input corpus must be annotated for semantics. Such corpora are expensive, difficult to obtain and, their size and quality directly affects the quality of the resulting system, i.e., larger, higher quality and correspondingly more difficult to obtain and so more expensive corpora yield a higher quality spoken language dialog system. [0009]
  • Because of their many advantages, spoken language dialog systems development is an active area of current research and promises many products with a variety of applications. Such products may be used for receiving stock quotes, disseminating weather or yellow pages information, sending and receiving e-mail, as well as using a voice interface to browse the Internet. The main hurdle in getting new products to market is the time and expertise required to create or adapt necessary spoken dialog components, such as grammars, speech recognizers and dialog managers for new domains. Whoever can best streamline the process of porting these components to new domains will have a distinct advantage over others in this competitive field. [0010]
  • Thus, there is a need for an easy way to automatically create declarative domain information in a form that reflects a domain expert's conceptualization of the domain.[0011]
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The foregoing and other objects, aspects and advantages will be better understood from the following detailed description of a preferred embodiment of the invention with reference to the drawings in which: [0012]
  • FIG. 1 is a flow diagram of this first step wherein domain objects and attributes are derived from available information; [0013]
  • FIG. 2 is a flow diagram showing how table columns are processed; [0014]
  • FIG. 3 is pseudocode corresponding to the first step of the preferred embodiment of the present invention in FIGS. 1 and 2. [0015]
  • FIGS. [0016] 4A-B show the second step wherein domain object nesting is determined such that domain objects serve as complex variable values for other domain objects.
  • FIG. 5 is pseudocode corresponding to the second step of the preferred embodiment of the present invention of the flow diagrams of FIGS. [0017] 4A-B.
  • DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT OF THE INVENTION
  • The present invention is a system, method and program product that allows any person, regardless of their level of domain model creation expertise to create a domain model from a given domain specification. The domain specification may be in the form of a relational database or Application Programming Interface (API). The domain specification contains information available to the preferred embodiment system regarding an application domain but, does not necessarily reflect a human expert's conceptualization of that information. The domain specification may contain functional elements, such as what are referred to as “bridging” tables in a relational database, that have no correlation in the real world but, only exist to facilitate database look-up. Typically, relational databases include only attributes that are string or integer values, each requiring an arbitrary identifier to relate one object to another. Thus, the domain model may include attributes with arbitrary nesting of complex values of objects and each object may have another object as its value. [0018]
  • In particular, the preferred embodiment system is a tool that creates nested structures with optional developer interaction and thus does not require inclusion of artifacts of arbitrary identifiers and bridging tables. Advantageously, the preferred embodiment tool assigns default names drawn from the names of tables and columns in the relational database and, then, allows renaming of objects and attributes from these default names. Thus, a default domain model may be created from a domain specification such as a relational database or API. Then, optionally, a developer with any degree of expertise may interact with the system to further refine and develop the result as desired. [0019]
  • So, first, an intuitive and flexible representation of the domain knowledge is derived from a domain specification. The domain specification includes whatever information is available and, typically, is a relational database or an API. From this domain specification, a default set of objects is extracted, and for each object, a default set of attributes also is extracted. Using, for example, a relational database as an input, each database table is converted into a default domain object with the name of the particular table as the default name of the object. Initially, for each table, each column is a default domain attribute with the name of the column as the default name of the attribute. Correspondingly, for an API input, the default object names are extracted from the names of function arguments and, the names of attributes are extracted from the functions themselves. [0020]
  • FIG. 1 is a flow diagram of this first step [0021] 100, providing an example wherein domain objects and attributes are derived from available information, i.e., in this example from tables and columns in a database. First, processing the domain specification begins in step 102 as one of the tables is selected from the database, correspondingly, for an API, a function argument would be selected. Then, in step 104 the developer is asked whether the domain model should contain a domain object corresponding to the selected table. If the developer responds yes, then, in step 106 a domain object is created. Object naming begins in step 108 wherein a default name, i.e., the table name or API function name, is presented to the developer and the developer may either accept the default name or provide a name. If the developer decides to provide a name for the object, then, in step 110 the developer's name is attached to the object. Otherwise, the default name is attached to the object.
  • Next, attributes are identified and named for the domain object beginning in step [0022] 112. So, in this example, attributes for the object, the table in this example, are identified by selecting each column and assigning attribute names to selected columns where appropriate. Correspondingly, for an API, function names are extracted and attached as attribute names. In step 114, the object is added to the domain model. In step 116, the database is checked for any remaining unselected potential objects (tables or API functions) and, if any are found, returning to step 102, the next database table or API function is selected and processed. Processing the domain specification continues until all potential objects are either included in or excluded from the domain model. So, when all the tables in the database either have been included as domain objects or rejected and, not included as domain objects, the preferred embodiment tool proceeds to the second step 200, as described herein below, wherein domain object nesting is determined.
  • An inexperienced developer with no expertise in a particular domain may choose to accept defaults, resulting in creating a default domain model. Although the default domain model is completely functional, it may not be the best conceptualization of the domain knowledge. So, even though the default domain model can be used in the creation of grammars for the given domain, those created grammars may be sub-optimal. By contrast, a more experienced domain developer with a higher level of domain expertise may reject the defaults, selecting other name variations from choices presented by the preferred embodiment system. [0023]
  • FIG. 2 is a flow diagram showing how attribute names (for table columns in this example) are processed in step [0024] 112. First, in step 1122, columns are selected from the table one at a time. Then, in step 1124, the developer is asked whether to include a domain attribute for the selected column in the domain object. If the developer wishes to include a domain attribute, then in step 1126 the developer is allowed to accept the domain attribute or, in step 1128 the developer may name the domain attribute. In step 1130 two lists, a value list and a value type list, are created and initialized (as empty) for the domain attribute. Then, in step 1132, each entry is selected from the column, one entry at a time. In step 1134, the selected entry is checked to determine if it is contained in the value type list. If it is not found, a value type is added for the selected entry to the value type list in step 1136. Next, in step 1138 the value list is checked to determine whether a value is included for the selected entry. If not, in step 1140, a value is added to the value list. Next, in step 1142 the domain attribute is added to the domain object. In step 1144 the column is checked for any unselected entries and, if unselected entries remain, returning to step 1132, one is selected. However, if all of the column entries have been selected, then, in step 1146 the table is checked to determine if any unselected columns remain and, if so, returning to step 1122, an unselected column is selected. Once all columns have been selected, then, continuing in step 116, the object is added to the domain model.
  • FIG. 3 is pseudocode of the first step of the preferred embodiment of the present invention corresponding to the flow diagrams of FIG. 1. [0025]
  • Continuing to the second step [0026] 200 these named objects and attributes describing the domain are presented to the developer, one object at a time, and within each object, one attribute at a time. If the developer perceives that a given default attribute is an arbitrary identifier of another object, the developer may choose to replace the particular default attribute with an instance of that other object resulting in a nested structure. Similarly, if the developer perceives that a given default object corresponds to a bridging table in a relational database, the developer may use preferred embodiment tool to replace references to that bridging table in each of the referring objects with a direct reference to the bridged to object. At all stages, the developer may reject the default names suggested for objects and attributes by the preferred embodiment tool, selecting instead more intuitive names.
  • FIGS. [0027] 4A-B show the second step 200 wherein domain object nesting is determined such that domain objects serve as complex variable values for other domain objects. FIG. 5 is pseudocode corresponding to the flow chart of the second step 200 of FIGS. 4A-B. First, in step 2002, domain objects are selected one at a time from the domain model. Then, beginning in step 2004, all remaining unselected domain objects are selected, one at a time, checked against the first domain object for attributes with conflicting value types and, names are assigned to non-conflicting attributes. So, in step 2004 a second domain object is selected from the domain model. In step 2006 identically named domain attributes in both the first selected domain object (i.e., selected in step 2002) and the second selected domain object (i.e., selected in step 2004) are identified. In step 2008 each of the identified identically named attributes are selected one at a time. In step 2010, the attribute type for the two identically named attributes are checked to determine whether they conflict. If they are non-conflicting attribute types, then, in step 2012 the developer is asked whether the first object should include a domain attribute with a complex value that is an instance of the second domain object. If the developer responds yes, then, in step 2014 a new domain attribute name is created for the developer which defaults to the attribute name of the second domain object attribute.
  • Continuing, in step [0028] 2016 the developer is asked if the default name is acceptable. If not, then, in step 2018 the developer enters a new domain attribute. Otherwise, the default name is used. Next in step 2020, the value type of the new domain attribute name is set to the value type of the second domain object. In step 2022, the new domain attribute is included in the first domain object. Then, in step 2024, the previously identified identically named attributes are checked to determine whether any identically named attributes still remain unselected. If unselected attributes remain, returning to step 2008 the next name of such identified identically named attribute is selected.
  • When in step [0029] 2010 the type of the attribute selected from the first domain object conflicts with the attribute type of the identically named attribute of the second selected object, then, in step 2026, the developer is informed of a name clash. The developer is then prompted in step 2028 to rename one or both of the domain attributes and, optionally, the developer may be offered default attribute names created using the domain object names as prefixes for the conflicting domain attributes. Once renamed, either using the default names or developer supplied names, continuing to step 2040, the renamed attributes are propagated through the domain model. Again, returning to step 2024, the previously identified identical attributes are checked for any that remain unselected.
  • If no conflict is found in step [0030] 2010, but, in step 2012 the developer decides that the first domain object should not include a domain attribute that is an instance of the second domain object, then in step 2028 the developer is prompted to rename one or both of the attributes. Once, in step 2024, it is determined that all identified identical attributes have been selected, then, in step 2032 a check is made whether other potential objects remain that have not been paired with the first object. If other potential objects remain unpaired, then, returning to step 2004, one of the other remaining objects are selected.
  • When, in step [0031] 2032, all other objects are found to have been paired with the first selected object, then, in step 2034, the objects are checked to see if any have yet been selected for comparison against other objects, i.e., as first objects. If some objects remain, then returning to step 2002, one of the remaining objects are selected. Otherwise, in step 2036, the domain model is complete.
  • As the domain model develops, it is displayed to the developer in an intuitive format, for example, using a graphical user interface (GUI.) One such intuitive format is an Attribute-Value Matrix (AVM). An AVM is a set of feature-value pairs, where each feature specifies a given slot or location of an object and the corresponding value is a filler for that slot, i.e., information stored at that location. A value in an AVM structure may itself be an AVM structure, thus allowing for any degree of nesting. AVM structures provide a formalized and yet intuitive way to display domain information and are relatively transparent to the developers, regardless of the developer's expertise. [0032]
  • While the invention has been described in terms of preferred embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims. [0033]

Claims (31)

I claim:
1. A method of creating a domain model, said method being usable by persons inexperienced in creating domain models to create a domain model, said method comprising the steps of:
deriving a representation of domain knowledge from a domain specification, said representation being a plurality of domain objects, each of said domain objects including one or more attributes; and
nesting said domain objects, wherein one or more of said domain objects point to one or more other domain objects.
2. A method as in claim 1, wherein the step of deriving the representation of domain knowledge comprises the steps of:
a) selecting an object from said domain specification;
b) naming said selected object;
c) selecting attributes in said selected object; and
d) assigning names to selected ones of said attributes.
3. A method as in claim 2, wherein the step (a) of selecting the object further comprises:
i) selecting a candidate object from said domain specification; and
ii) determining whether to include said selected candidate object in said representation, candidate objects determined to be included in said representation being selected objects.
4. A method as in claim 3, wherein as a name is provided for said selected object in step (b), said provided name is presented to a developer for acceptance, said presented name being a default object name.
5. A method as in claim 4, wherein when said developer rejects said default object name, said developer assigns an object name to said selected object.
6. A method as in claim 5, wherein the step of deriving the representation further comprises the step of:
e) repeating steps a-d until all candidate objects have been selected in step (a)(i).
7. A method as in claim 6, wherein the step (c) of selecting attributes further comprises:
i) selecting an attribute candidate for said selected object; and
ii) determining whether to include said attribute candidate in said representation, attribute candidates determined to be included being selected attributes.
8. A method as in claim 7, wherein the step (d) of selectively naming the attributes comprises presenting a default attribute name to said developer, said developer selectively accepting said attribute name.
9. A method as in claim 8, wherein when said developer rejects said default attribute name, said developer assigns an attribute name.
10. A method as in claim 7, wherein the candidate objects are tables in a relational database, attribute candidates are columns in said tables and step (a)(ii) of determining whether to include a selected table comprises presenting said selected table to said developer, said developer deciding whether said table is included as a domain object; and wherein, the step (c)(ii) of determining whether to include attribute candidates comprises presenting columns from said table to said developer, said developer deciding whether to include said column as an attribute.
11. A method as in claim 1, wherein the step of nesting domain objects comprises the steps of:
a) pairing domain objects;
b) identifying attributes having identical names within said paired objects;
c) identifying conflicting identically named attributes; and
d) renaming said conflicting attributes.
12. A method as in claim 11, wherein the step (c) of identifying conflicting identically named attributes further comprises:
i) identifying non-conflicting attributes in at least two objects;
ii) including in one or more of the at least two objects an instance of a selected one of the identically named attributes.
13. A method as in claim 12, wherein conflicting attributes have conflicting value types and non-conflicting attributes have non-conflicting value types.
14. A method as in claim 13, wherein the included instance is given a new domain attribute name.
15. A method as in claim 14, wherein the value type of the new domain attribute is set to the value type of the other of said non-conflicting attributes.
16. A system usable by domain developers having any domain development skill level to interactively create domain models, said system comprising:
means for automatically deriving a representation of domain knowledge from a domain specification, said representation being a plurality of domain objects, each of said domain objects including one or more attributes; and
means for automatically nesting said domain objects, wherein one or more of said domain objects points to one or more other domain objects.
17. A system as in claim 16, wherein the means for deriving the representation of domain knowledge comprises:
means for selecting an object from said domain specification and presenting said object to a developer;
means for selecting attributes in selected objects and presenting said attributes to said developer; and
means for assigning names to selected objects and selected attributes.
18. A system as in claim 17, wherein the means for assigning names comprises:
means for deriving a default name;
means for presenting said default name to said developer; and
means for receiving an alternate name from said developer.
19. A system as in claim 18, wherein the developer decides whether to include the presented object in a domain model, included objects being selected objects.
20. A system as in claim 18, wherein the developer decides whether to include the presented attributes in the domain model, included attributes being selected attributes.
21. A system as in claim 16, wherein the domain object nesting means comprises:
means for identifying attributes having identical names within said domain objects;
means for identifying conflicting attributes with identical names; and
means for renaming identified conflicting attributes.
22. A system as in claim 21, wherein the domain nesting means further comprises:
means for pairing objects; and
means for comparing value types of identically named attributes in paired said objects.
23. A system as in claim 22, further comprising means for assigning a value type to attributes.
24. A computer program product for enabling a domain developer to create domain models, regardless of the domain developer's skill level, said computer program product comprising a computer usable medium having computer readable program code thereon, said computer readable program code comprising:
computer readable program code means for automatically deriving a representation of domain knowledge from a domain specification, said representation being a plurality of domain objects, each of said domain objects including one or more attributes; and
computer readable program code means for automatically nesting said domain objects, wherein one or more of said domain objects points to one or more other domain objects.
25. A computer readable program code means for enabling a domain developer to create domain models as in claim 24, wherein the computer readable program code means for deriving the representation of domain knowledge comprises:
computer readable program code means for selecting an object from said domain specification and presenting said object to a developer;
computer readable program code means for selecting attributes in selected objects and presenting said attributes to said developer; and
computer readable program code means for assigning names to selected objects and selected attributes.
26. A computer readable program code means for enabling a domain developer to create domain models as in claim 25, wherein the computer readable program code means for assigning names comprises:
computer readable program code means for deriving a default name;
computer readable program code means for presenting said default name to said developer; and
computer readable program code means for receiving an alternate name from said developer.
27. A computer readable program code means for enabling a domain developer to create domain models as in claim 26, further comprising:
computer readable program code means for allowing the developer to decide whether to include the presented object in a domain model, included objects being selected objects.
28. A computer readable program code means for enabling a domain developer to create domain models as in claim 27, further comprising:
computer readable program code means for allowing the developer to decide whether to include the presented attributes in the domain model, included attributes being selected attributes.
29. A computer readable program code means for enabling a domain developer to create domain models as in claim 28, wherein computer readable program code means for domain object nesting comprises:
computer readable program code means for identifying attributes having identical names within different said domain objects;
computer readable program code means for identifying conflicting attributes with identical names; and
computer readable program code means for renaming identified conflicting attributes.
30. A computer readable program code means for enabling a domain developer to create domain models as in claim 29, wherein the computer readable program code means for domain nesting further comprises:
computer readable program code means for pairing domain objects; and
computer readable program code means for comparing value types of identically named attributes in paired said domain objects.
31. A computer readable program code means for enabling a domain developer to create domain models as in claim 30, further comprising computer readable program code means for selectively assigning value types to attributes.
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Cited By (97)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060178868A1 (en) * 2005-01-14 2006-08-10 Classified Ventures Methods and systems for generating natural language descriptions from data
US7366655B1 (en) * 2003-04-02 2008-04-29 At&T Corp. Method of generating a labeling guide for spoken dialog services
US20100042404A1 (en) * 2004-01-09 2010-02-18 At&T Corp. Method for building a natural language understanding model for a spoken dialog system
US20130110518A1 (en) * 2010-01-18 2013-05-02 Apple Inc. Active Input Elicitation by Intelligent Automated Assistant
US8977255B2 (en) 2007-04-03 2015-03-10 Apple Inc. Method and system for operating a multi-function portable electronic device using voice-activation
US9190062B2 (en) 2010-02-25 2015-11-17 Apple Inc. User profiling for voice input processing
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US9431006B2 (en) 2009-07-02 2016-08-30 Apple Inc. Methods and apparatuses for automatic speech recognition
US9430667B2 (en) 2014-05-12 2016-08-30 Microsoft Technology Licensing, Llc Managed wireless distribution network
US9477625B2 (en) 2014-06-13 2016-10-25 Microsoft Technology Licensing, Llc Reversible connector for accessory devices
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US9520127B2 (en) 2014-04-29 2016-12-13 Microsoft Technology Licensing, Llc Shared hidden layer combination for speech recognition systems
US9529794B2 (en) 2014-03-27 2016-12-27 Microsoft Technology Licensing, Llc Flexible schema for language model customization
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9589565B2 (en) 2013-06-21 2017-03-07 Microsoft Technology Licensing, Llc Environmentally aware dialog policies and response generation
US9614724B2 (en) 2014-04-21 2017-04-04 Microsoft Technology Licensing, Llc Session-based device configuration
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9626955B2 (en) 2008-04-05 2017-04-18 Apple Inc. Intelligent text-to-speech conversion
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US9646614B2 (en) 2000-03-16 2017-05-09 Apple Inc. Fast, language-independent method for user authentication by voice
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US9697200B2 (en) * 2013-06-21 2017-07-04 Microsoft Technology Licensing, Llc Building conversational understanding systems using a toolset
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9717006B2 (en) 2014-06-23 2017-07-25 Microsoft Technology Licensing, Llc Device quarantine in a wireless network
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9728184B2 (en) 2013-06-18 2017-08-08 Microsoft Technology Licensing, Llc Restructuring deep neural network acoustic models
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US9874914B2 (en) 2014-05-19 2018-01-23 Microsoft Technology Licensing, Llc Power management contracts for accessory devices
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9953088B2 (en) 2012-05-14 2018-04-24 Apple Inc. Crowd sourcing information to fulfill user requests
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US9971774B2 (en) 2012-09-19 2018-05-15 Apple Inc. Voice-based media searching
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US10079014B2 (en) 2012-06-08 2018-09-18 Apple Inc. Name recognition system
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10111099B2 (en) 2014-05-12 2018-10-23 Microsoft Technology Licensing, Llc Distributing content in managed wireless distribution networks
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US10269345B2 (en) 2016-06-11 2019-04-23 Apple Inc. Intelligent task discovery
US10276170B2 (en) 2010-01-18 2019-04-30 Apple Inc. Intelligent automated assistant
US10289433B2 (en) 2014-05-30 2019-05-14 Apple Inc. Domain specific language for encoding assistant dialog
US10297253B2 (en) 2016-06-11 2019-05-21 Apple Inc. Application integration with a digital assistant
US10318871B2 (en) 2005-09-08 2019-06-11 Apple Inc. Method and apparatus for building an intelligent automated assistant
US10356243B2 (en) 2015-06-05 2019-07-16 Apple Inc. Virtual assistant aided communication with 3rd party service in a communication session
US10354011B2 (en) 2016-06-09 2019-07-16 Apple Inc. Intelligent automated assistant in a home environment
US10366158B2 (en) 2015-09-29 2019-07-30 Apple Inc. Efficient word encoding for recurrent neural network language models
US10410637B2 (en) 2017-05-12 2019-09-10 Apple Inc. User-specific acoustic models

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2003213747A1 (en) * 2002-03-07 2003-09-22 Honeywell Inc. Interaction design system
CA2387452A1 (en) * 2002-05-24 2003-11-24 Petr Hejl Developing and running selected applications in communications
US20050165599A1 (en) * 2004-01-23 2005-07-28 Dale Russell Method and apparatus for generating a translation table
US20060288326A1 (en) * 2005-05-25 2006-12-21 Honeywell International Inc. Domain modeling system and method
US20060271856A1 (en) * 2005-05-25 2006-11-30 Honeywell International Inc. Interface design system and method with integrated usability considerations
US7590649B2 (en) * 2005-12-20 2009-09-15 At&T Intellectual Property, I,L.P. Methods, systems, and computer program products for implementing intelligent agent services
US7627661B2 (en) * 2005-12-20 2009-12-01 At&T Intellectual Property, I, L.P. Methods, systems, and computer program products for implementing ontological domain services
US7725308B2 (en) * 2006-06-07 2010-05-25 Motorola, Inc. Interactive tool for semi-automatic generation of a natural language grammar from a device descriptor
US8813101B2 (en) * 2007-03-28 2014-08-19 Microsoft Corporation Software technique to correlate conceptually similar entities
US7734659B2 (en) * 2007-06-01 2010-06-08 United Technologies Corporation System and method for creating an object model
US10417073B2 (en) 2017-04-12 2019-09-17 Bank Of America Corporation Application server deployment system for domain generation and testing with an administrative server virtual machine and managed server virtual machines

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5875440A (en) * 1997-04-29 1999-02-23 Teleran Technologies, L.P. Hierarchically arranged knowledge domains
US6226792B1 (en) * 1998-10-14 2001-05-01 Unisys Corporation Object management system supporting the use of application domain knowledge mapped to technology domain knowledge

Cited By (123)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9646614B2 (en) 2000-03-16 2017-05-09 Apple Inc. Fast, language-independent method for user authentication by voice
US7366655B1 (en) * 2003-04-02 2008-04-29 At&T Corp. Method of generating a labeling guide for spoken dialog services
US7729902B1 (en) 2003-04-02 2010-06-01 At&T Intellectual Property Ii, L.P. Method of generation a labeling guide for spoken dialog services
US20100042404A1 (en) * 2004-01-09 2010-02-18 At&T Corp. Method for building a natural language understanding model for a spoken dialog system
US7933766B2 (en) * 2004-01-09 2011-04-26 At&T Intellectual Property Ii, L.P. Method for building a natural language understanding model for a spoken dialog system
US7930169B2 (en) * 2005-01-14 2011-04-19 Classified Ventures, Llc Methods and systems for generating natural language descriptions from data
US20060178868A1 (en) * 2005-01-14 2006-08-10 Classified Ventures Methods and systems for generating natural language descriptions from data
US10318871B2 (en) 2005-09-08 2019-06-11 Apple Inc. Method and apparatus for building an intelligent automated assistant
US9117447B2 (en) 2006-09-08 2015-08-25 Apple Inc. Using event alert text as input to an automated assistant
US8930191B2 (en) 2006-09-08 2015-01-06 Apple Inc. Paraphrasing of user requests and results by automated digital assistant
US8942986B2 (en) 2006-09-08 2015-01-27 Apple Inc. Determining user intent based on ontologies of domains
US8977255B2 (en) 2007-04-03 2015-03-10 Apple Inc. Method and system for operating a multi-function portable electronic device using voice-activation
US10381016B2 (en) 2008-01-03 2019-08-13 Apple Inc. Methods and apparatus for altering audio output signals
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9626955B2 (en) 2008-04-05 2017-04-18 Apple Inc. Intelligent text-to-speech conversion
US9865248B2 (en) 2008-04-05 2018-01-09 Apple Inc. Intelligent text-to-speech conversion
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US10108612B2 (en) 2008-07-31 2018-10-23 Apple Inc. Mobile device having human language translation capability with positional feedback
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US9431006B2 (en) 2009-07-02 2016-08-30 Apple Inc. Methods and apparatuses for automatic speech recognition
US10283110B2 (en) 2009-07-02 2019-05-07 Apple Inc. Methods and apparatuses for automatic speech recognition
US10276170B2 (en) 2010-01-18 2019-04-30 Apple Inc. Intelligent automated assistant
US20130110518A1 (en) * 2010-01-18 2013-05-02 Apple Inc. Active Input Elicitation by Intelligent Automated Assistant
US9548050B2 (en) 2010-01-18 2017-01-17 Apple Inc. Intelligent automated assistant
US20130117022A1 (en) * 2010-01-18 2013-05-09 Apple Inc. Personalized Vocabulary for Digital Assistant
US8670979B2 (en) * 2010-01-18 2014-03-11 Apple Inc. Active input elicitation by intelligent automated assistant
US8892446B2 (en) 2010-01-18 2014-11-18 Apple Inc. Service orchestration for intelligent automated assistant
US8903716B2 (en) * 2010-01-18 2014-12-02 Apple Inc. Personalized vocabulary for digital assistant
US9318108B2 (en) 2010-01-18 2016-04-19 Apple Inc. Intelligent automated assistant
US10049675B2 (en) 2010-02-25 2018-08-14 Apple Inc. User profiling for voice input processing
US9190062B2 (en) 2010-02-25 2015-11-17 Apple Inc. User profiling for voice input processing
US9633660B2 (en) 2010-02-25 2017-04-25 Apple Inc. User profiling for voice input processing
US10102359B2 (en) 2011-03-21 2018-10-16 Apple Inc. Device access using voice authentication
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9953088B2 (en) 2012-05-14 2018-04-24 Apple Inc. Crowd sourcing information to fulfill user requests
US10079014B2 (en) 2012-06-08 2018-09-18 Apple Inc. Name recognition system
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9971774B2 (en) 2012-09-19 2018-05-15 Apple Inc. Voice-based media searching
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9966060B2 (en) 2013-06-07 2018-05-08 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
US9728184B2 (en) 2013-06-18 2017-08-08 Microsoft Technology Licensing, Llc Restructuring deep neural network acoustic models
US10304448B2 (en) 2013-06-21 2019-05-28 Microsoft Technology Licensing, Llc Environmentally aware dialog policies and response generation
US9697200B2 (en) * 2013-06-21 2017-07-04 Microsoft Technology Licensing, Llc Building conversational understanding systems using a toolset
US9589565B2 (en) 2013-06-21 2017-03-07 Microsoft Technology Licensing, Llc Environmentally aware dialog policies and response generation
US9529794B2 (en) 2014-03-27 2016-12-27 Microsoft Technology Licensing, Llc Flexible schema for language model customization
US9614724B2 (en) 2014-04-21 2017-04-04 Microsoft Technology Licensing, Llc Session-based device configuration
US9520127B2 (en) 2014-04-29 2016-12-13 Microsoft Technology Licensing, Llc Shared hidden layer combination for speech recognition systems
US10111099B2 (en) 2014-05-12 2018-10-23 Microsoft Technology Licensing, Llc Distributing content in managed wireless distribution networks
US9430667B2 (en) 2014-05-12 2016-08-30 Microsoft Technology Licensing, Llc Managed wireless distribution network
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9874914B2 (en) 2014-05-19 2018-01-23 Microsoft Technology Licensing, Llc Power management contracts for accessory devices
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US10169329B2 (en) 2014-05-30 2019-01-01 Apple Inc. Exemplar-based natural language processing
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US10083690B2 (en) 2014-05-30 2018-09-25 Apple Inc. Better resolution when referencing to concepts
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US10289433B2 (en) 2014-05-30 2019-05-14 Apple Inc. Domain specific language for encoding assistant dialog
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US9477625B2 (en) 2014-06-13 2016-10-25 Microsoft Technology Licensing, Llc Reversible connector for accessory devices
US9717006B2 (en) 2014-06-23 2017-07-25 Microsoft Technology Licensing, Llc Device quarantine in a wireless network
US9668024B2 (en) 2014-06-30 2017-05-30 Apple Inc. Intelligent automated assistant for TV user interactions
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US9986419B2 (en) 2014-09-30 2018-05-29 Apple Inc. Social reminders
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US10311871B2 (en) 2015-03-08 2019-06-04 Apple Inc. Competing devices responding to voice triggers
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10356243B2 (en) 2015-06-05 2019-07-16 Apple Inc. Virtual assistant aided communication with 3rd party service in a communication session
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US10366158B2 (en) 2015-09-29 2019-07-30 Apple Inc. Efficient word encoding for recurrent neural network language models
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10354011B2 (en) 2016-06-09 2019-07-16 Apple Inc. Intelligent automated assistant in a home environment
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10297253B2 (en) 2016-06-11 2019-05-21 Apple Inc. Application integration with a digital assistant
US10269345B2 (en) 2016-06-11 2019-04-23 Apple Inc. Intelligent task discovery
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10410637B2 (en) 2017-05-12 2019-09-10 Apple Inc. User-specific acoustic models

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